Albedic Meanderings

I’ve been considering the nature of the relationship between the albedo and temperature. I have hypothesized elsewhere that variations in tropical cloud albedo are one of the main mechanisms that maintain the global surface temperature within a fairly narrow range (e.g. within ± 0.3°C during the entire 20th Century). To provide observational support for the hypothesis, I’ve been looking at the relationship between temperature and albedo, both globally and more particularly in the tropics.

To start with, the “albedo” of an object is a number from 0.0 to 1.0 that measures the fraction of solar radiation that is reflected from the surface of the object. It’s often given as a fraction, although I prefer it as a percentage. The albedo of the earth is about 0.29, meaning 29% of the sunlight is reflected back to space. Figure 1 shows the average albedo around the planet.

Figure 1. Average total albedo, including surface and cloud albedo. Calculations in the heading are for the northern and southern hemispheres (NH, SH) the tropics (Trop), the Arctic (Arc), the Antarctic (Ant), and the land and ocean.

Figure 1 shows some salient features. One is the inter-tropical convergence zone (ITCZ), which is the light green area just north of the Equator. It marks (as the name suggests) the average boundary between the northern and southern hemispheric air masses. The ITCZ is the area of deep tropical convection, the area increased clouds just above the Equator. To verify that the oceanic variations we are looking at are a result of cloud albedo rather than ocean surface albedo, we can compare Figure 1 with Figure 2, which shows the surface albedo.

Figure 2. Average surface albedo only.

As you can see, the average albedo of the ocean varies little, other than increasing slightly from equator to pole. The combination of the two figures highlights an albedic mystery—the total albedo of the northern and southern hemispheres are identical to three significant digits. This is clearly the result of the clouds, as the surface albedos of the two hemispheres are quite different. However, the mechanisms involved in the rebalancing are unclear. It does emphasize the responsive nature of the cloud albedo.

Now, as I said above, I wanted to look at the relationship between temperature and albedo. I started by looking at how the relationship breaks out spatially. Figure 3 shows the correlation between average temperature and average albedo. “Correlation” is a number that can vary between -1.0 and +1.0. A correlation of plus one indicates perfect positive correlation (both either go up or go down together). A correlation of minus one indicates perfect negative correlation (when one goes up the other goes down, but still in step with each other).

Figure 3. Correlation between temperature and albedo. The area outlined in red is analyzed separately below in Figures 5 & 6.

As you can see, the northern hemisphere land towards the poles is strongly negatively correlated with temperature. This is because as the northern land warms, the ice and snow melts and the plants grow. Both of these changes lower the solar reflectivity (albedo). In the tropics, on the other hand, there are a number of large areas that are positively correlated with temperature.

Next, I took a look at the general relationship between the temperature and the albedo. I wanted to look in particular at what is happening in the ocean. Figure 4 shows that relationship.

Figure 4. Gridcell by gridcell comparison of average albedo and average ocean temperature. Temperatures below freezing are of ice-covered ocean.

Now, this is most interesting. The warmer the ocean gets, the lower the albedo goes, a negative correlation … except when the temperature gets over about 26°. Above that, the warmer it gets, the higher the albedo goes. This is the tropical area shown in Figure 3 where there is positive correlation between the albedo and the temperature. This is exactly the mechanism that I have proposed, that increasing tropical temperatures cause increasing albedo and thus help to regulate the global temperature. I say that this is due to a combination of both earlier and stronger daily emergence of the cumulus, thunderstorm, and squall line regimes.

However, it could be fairly argued that in Figure 4 we’re not looking at temperature and albedo changes in one location. Instead, we’re looking at average values in a host of different locations. So it might be that the “hook” at the high temperatures doesn’t reflect what is happening as the temperature changes in each individual location.

To see if this is so, I’ve invented a kind of plot that I call a “Lissajous scatterplot”. Or maybe I didn’t invent it, but I’ve never seen one before. It is a combination of Lissajous figures and a scatterplot. Instead of displaying the average for each gridcell, I display the Lissajous figure for that gridcell. And what is a Lissajous figure when it’s just sitting at home by the fire?

A Lissajous figure is a display of two cyclical values, with one shown on the horizontal axis and the other on the vertical axis. As usual there’s a good description at Wolfram Mathworld, and Wolfram also has an interesting interactive demonstration of the Lissajous figures here.

I use the monthly average values of two cyclical variables to make a Lissajous figure. Here, for example, is the Lissajous figure for temperature and albedo for the gridcell located at 45N 80W:

Figure 5. Lissajous figure, monthly average temperature versus monthly average albedo. The location is near the Great Lakes in North America.

As you can see, in that particular location, as the temperature goes up, the albedo goes down.

So with that as Lissajous prologue, Figure 6 shows a Lissajous scatterplot of the temperature and albedo of an area of the tropical Pacific. This is the area of the Pacific outlined in red in Figure 3. In essence Figure 6 shows the lower right end of the graph shown in Figure 4, but with Lissajous figures for each gridcell rather than dots representing the gridcell averages.

Figure 6. Lissajous scatterplot, showing the monthly changes in tropical Pacific temperatures and albedo. The area of the analysis is outlined in red in Figure 3. Each gridcell is represented by a Lissajous figure showing how monthly average albedo varies with monthly average temperature

Recall that I am using this method to see if the “hook” in the high-temperature region of Figure 3 was actually reflected in the temperature and albedo changes in each individual location over time. And indeed, the change in the direction of the relationship with the rising temperature shown in Figure 3 is totally borne out by Figure 6. Albedo is dropping as temperatures rise, but only up to about 26°C. As temperatures start rising above 26°C the albedo just goes through the roof.

Finally, how much more sunlight is reflected by this increase in albedo? Figure 7 shows a Lissajous scatterplot of the reflected sunlight versus temperature:

Figure 7. Lissajous scatterplot, as in Figure 6 but showing the monthly changes in tropical Pacific temperatures and reflected sunlight. The area of the analysis is outlined in red in Figure 3.

Figure 7 makes it clear just how much difference the change in albedo makes. The white dashed line shows the approximate trend of the high-temperature section of the graph. The slope of that line is no less than 60W/m2 per °C. In other words, in the warmest tropical regions, for each degree that the temperature warms, the albedo cuts down the incoming sunlight by about 60 W/m2.

My conclusion? The “hook” in the high temperature end of the temperature/albedo graph is evidence that cloud albedo is part of the system that places a limit on how warm the tropical ocean is able to get. When the temperature gets above a certain point, increased clouds cut way back on the incoming energy. The “hook” also provides evidence of some kind of “set point” around 26° – 27°C, with temperatures warmer than that being cooled and temperatures cooler than that being warmed by the variation in albedo.

The albedo data is thus strong support for my hypothesis that the timing and strength of the daily onset of the tropical cumulus and cumulonimbus regimes exercises a strong control on the amount of incoming energy. The presence of large areas of tropical ocean with a positive correlation between temperature and albedo lead to a naturally stable system … which will likely be the subject of my next post, unless I’m once again distracted by … oooh, shiny!

Regards to all, keep the pedal to the metal …

w.

My Customary Request: If you disagree with someone, please QUOTE THEIR EXACT WORDS that you disagree with so we can all understand your precise objections.

Data: Once again I’ve used the CERES EBAF satellite-based radiation dataset.

With my background in Systems Science, I see feedback mechanisms everywhere. One develops a nose for them, and, in the natural world, as in engineering, most of them seem to be negative (stabilizing) mechanisms, which attenuate forcings.
You seem to have identified a non-obvious but doubtless very important negative (stabilizing) feedback mechanism, Willis.
There are many other negative feedback mechanisms at work, too. Some of them are obvious, others less so.1. Most basically, of course, the warmer things get, the faster they lose heat. But, also:2. As temperatures go up, evaporation at the surface increases. That removes “heat of evaporation” from the surface. Moist air is lighter than dry air (contrary to intuition), so the moist air rises until the moisture condenses into water droplets or ice flecks, as clouds, releasing the latent heat which was absorbed at the surface. Thus the water cycle is a classic phase-change refrigeration cycle, removing heat from the surface, and releasing it aloft, just as the Freon phase-change refrigeration cycle cools your refrigerator.
Anything which increases surface evaporation (such as warmer water, or reduced ice cover) increases water-cycle cooling.
Because increase surface temperatures make the cycle run faster, it is a negative feedback mechanism, cooling the surface faster, as temperatures go up.3. As levels of The Precious Air Fertilizer (CO2) levels go up, so do plant growth rates. That removes more CO2 from the air, attenuating the increase in CO2 — another negative feedback mechanism.4. At extreme latitudes, warmer water reduces ice cover. That increases evaporation, making the water cycle run faster, and cooling the water (#2, above). It also allows wave action to create turbulence beneath the surface, allowing faster exchange between water at the surface (cooled by evaporation) and water beneath the surface, thereby helping to cool the water.5. The additional evaporation due to more open water also apparently causes additional cloud cover, increasing albedo at altitude, and additional lake-effect/ocean-effect snowfall downwind. Some of that snow falls on the ice-sheets, increasing ice accumulation, and some of it falls on land, increasing albedo, decreasing land temperatures, and prolonging winter — another negative (stabilizing) feedback mechanism, by which additional warmth causes additional cooling.
Note: that snow accumulation is a big deal. The magnitude of ice accretion from snowfall on ice sheets was illustrated by the team which salvaged Glacier Girl from under 268 feet(!!) of accumulated ice, 50 years after she landed on the Greenland ice sheet.
But the negative feedback mechanism you’ve identified, Willis, is new to me. Very excellent work!

The albedo feedback for sea surface is positive for SST’s less than 26C at which point it rapidly becomes negative. This corresponds somewhat to a positive feedback excursion on an amplifier running into a power supply rail. The climate over the last million years has acted like a bistable circuit slamming into the positive and negative rails.
The bad news is that there is no apparent short term feedback mechanism for downward temperature excursions, which would explain why glacial periods are typically much longer than interglacial periods. The long term albedo negative feedback probably comes from the extreme dryness during the glacial period causing dust to be blown around and decreasing the albedo of the ice and snow.

One small correction/clarification: “additional cloud cover, increasing albedo at altitude,” isn’t necessarily a negative feedback mechanism (which reduces warming). At night and when the sun is near the horizon, additional cloud cover helps warm the surface. So if additional cloud cover results from reduced ice cover which results from warmer water, that means it’s a positive (rather than negative) feedback mechanism, at least when the sun is near or beneath the horizon.

One reason that 26C ay be the magic number for the inflection point is that is about where a degree rise in dew point causes more of reduction in air density than what is caused by raising the air temp one degree with no change in absolute humidity. Since the vapor pressure of water doubles for roughly every 10C increase (at least around 26C), it doesn’t take much of a dew point rise to have a large effect on convection and dew point will roughly be the sea surface temperature.
Willis’s findings make perfect sense to me.

Do not forget that the convective clouds are formed from condensed water vapour which removes a lot of surface heat through latent heat during evapouration. So latent heat, convective cloud and increased albedo all add to that negative feedback.

Also agree. This is Willis finest work. The hook suggests a true stabilizing process. Low temps let in more heat. Hi temps reduce the amount of heat allowed in. The graphs are spectacular.
It would be swell if the IPCC would pay some attention to this fine idea, given that the cloud albedo model, whatever that model turns out to be, is always going to be absolutely central to the GCM predictions.

Willis, your continued presentations about the emergent cloud/albedo phenomena acting as temperature buffers has been most instructive- thanks much.
Speaking of albedo, the Northern Hemisphere snow cover remains relatively high for this time of year.http://home.comcast.net/~ewerme/wuwt/cryo_compare.jpg

I’m afraid not, Cryosphere Today is having problems with the source of the snow cover data and as they say on their website:
“Note: snow cover data not updating … we hope to have a new data source by July, 2015.”

Let’s say for the tropics then, when CO2 doubling occurs and there is +3.7 W/m2 more in GHG forcing causing the temperature to rise by 1.0C, …
… your numbers indicate that Albedo would increase substantially resulting in a negative feedback of something like -35 W/m2 of sunlight reflected (with an offsetting OLR reduction caused by the increased clouds of about half that amount or +17.5 W/m2 which is what increased clouds do) so the net negative cloud forcing would be -17.5 W/m2 for the +3.7 W/m2 of CO2 doubled forcing.
The climate models and the theory assume there is +0.7/W/m2 of cloud feedback forcing per +3.7 W/m2 of increased GHG forcing while these numbers for the tropics say it should really be -17.5 W/m2 per +3.7 W/m2 of GHG forcing.

Mankind still understands very little about clouds, or their effects on climate and bless their pointy heads, the modellers seem to know as much as the rest of us, or willfully less as it suits their purpose. (Sorry, I can no longer give modelers too much benefit of the doubt, but I’m just some guy with an opinion.)

That’s why I’m at great pains to point out that what we’re seeing is not a simple negative feedback. Instead, it’s a governor, which can indeed reverse the sign. See my post, It’s Not About Feedback.
w.

It’s still a feedback mechanism, Willis, it’s just not a linear feedback mechanism.
A governor is a feedback mechanism. When engine speed goes up, the governor notices the increase, and cuts the fuel flow (or fuel & air) supply, to bring the engine speed back down. When engine speed goes down, the governor increases the fuel supply, to compensate.
If your governor is controlled by engine speed, then it cannot reverse the sign of the effect of increasing or decreasing drag on the engine or any other factor which affects engine speed. A governor can erase most of the effect, so that the engine speed under heavy drag is not much less than the engine speed with no load, but it can’t make the average engine speed be faster under load than with no load.
(Caveat: if there’s a delay between the engine speed change and the governor responding to it — and there always is some delay — that can cause instability, if the feedback amplification is too high [i.e., if the governor is too sensitive]. That can cause transient “overshoots” or even persistent oscillations in engine speed.)
The same is true for climate systems. If higher temperature causes an effect (such as increased cloud cover) which causes lower temperature, that can reduce some or even most of a forcing which increases temperature. But it cannot reverse the sign.
Think of your kitchen. Your thermostat may turn on the air conditioner to keep the kitchen temperature comfortable while you’re cooking, but It can’t make turning the oven on cause the kitchen to get colder.
Of course, if you had a governor which was controlled directly by engine drag, rather than by (or in addition to) engine speed, then you could, indeed, make a system in which engine speed was higher under load than under no load. Likewise, if you had a thermostat system which was tied to your oven controls, so that it could turn on the air conditioner in anticipation of the warming from the oven, you could make turning on the oven cause the kitchen to get colder. But that’s not the result of the warming from the oven, that’s just adding another function to your oven controls, so that turning on the oven turns on the air conditioner, too.
For there to be something like that going on in a climate system would require separate feedback mechanisms coupled to each of the many forcings which affect temperature, rather than driven by temperatures. So, for clouds, there would have to be a mechanism by which CO2 directly increases cloud cover (rather than by the intermediate agency of warming), a mechanism by which volcanic aerosols directly decrease cloud cover, a mechanism by which increased solar irradiance directly increases cloud cover, etc. That might be plausible for one or two exceptional forcings, but it is not plausible in the general case.

That’s why I’m at great pains to point out that what we’re seeing is not a simple negative feedback. Instead, it’s a governor, which can indeed reverse the sign. See my post, It’s Not About Feedback.
w.

daveburton June 3, 2015 at 2:52 pm

It’s still a feedback mechanism, Willis, it’s just not a linear feedback mechanism.

Thanks, Dave. That’s what I just said, except I called it a “simple negative feedback”.

A governor is a feedback mechanism.

I’m sorry, but that’s not so. In the current context, a governor is a mechanism that controls the throttle of a heat engine in order to set it to some specified operating condition. For example, the “cruise control” in a car is an example of a governor. It is a mechanism that controls the throttle of a car to set it to a certain speed over the ground.

When engine speed goes up, the governor notices the increase, and cuts the fuel flow (or fuel & air) supply, to bring the engine speed back down. When engine speed goes down, the governor increases the fuel supply, to compensate.

True … which is why it is not a simple feedback. The governor can push the throttle either way. Simple negative feedback can’t do that.

If your governor is controlled by engine speed, then it cannot reverse the sign of the effect of increasing or decreasing drag on the engine or any other factor which affects engine speed. A governor can erase most of the effect, so that the engine speed under heavy drag is not much less than the engine speed with no load, but it can’t make the average engine speed be faster under load than with no load.

You must hang out with some low-budget governors. In fact, in order to be able to control a system with significant lag (such as the climate), a governor needs to have “overshoot” … which means it has to do what you say can’t be done.
And this is why a thunderstorm functions as a governor and is not a feedback in any sense. It is able to drive the surface temperature down below the temperature at which the thunderstorm formed, something which you’ve deemed impossible. It can do this because it is a duel-fuel engine, and once it gets running it manufactures some of its own fuel … and there’s no “feedback” that can do that.
w.

Willis,
Dave is right about this. Negative feedback most certainly can ‘move the throttle’ in either direction; if the controlled variable is above the ‘set point’ then negative feedback will reduce the throttle. If it is below the set point, then negative feedback will increase the throttle. It is just proportional control, and proportional control (unless it is too sensitive/aggressive and the system oscillates) will always act to reduce, but not eliminate, the response to a perturbation. In other words, there will always remain a residual ‘offset’ which is proportional to the strength of the perturbing force, and inversely proportional to ‘sensitivity’ of the negative feedback. BTW, there are lots of kinds of governors, the most common of which is just a proportional negative feedback. More complicated governors include addition of an integration of the residual offset to the control signal, to gradually reduce that offset towards zero (PI control) A more sophisticated control scheme adds both integration of the offset and the first derivative of the offset (both multiplied by suitable constants) to the output signal (PID control). This reduces tendency to oscillate and so allows more ‘aggressive’ control, with smaller deviations from set point.

Dave is right about WHAT???
Was there some part of “QUOTE THEIR EXACT WORDS” that was too complex or something? Dave has made many statements. It’s totally unclear what you are agreeing with from Dave.
w.

Willis wrote (more or less), “[A governor is not a feedback mechanism.] In the current context, a governor is a mechanism that controls the throttle of a heat engine in order to set it to some specified operating condition. For example, the “cruise control” in a car is an example of a governor. It is… not a simple feedback. The governor can push the throttle either way. Simple negative feedback can’t do that.”
Actually, a cruise control is very commonly used in engineering classes and texts as an example of a feedback system. Here are some illustrations (mostly block diagrams) showing how it works:https://www.google.com/search?q=%22cruise+control%22+feedback+system&tbm=isch
Negative feedback does, indeed, “push the throttle either way.” For example, as CO2 levels go up, plants grow faster and use more CO2, thus attenuating the increase in CO2. But as CO2 levels go down, plants grow more slowly, and use less CO2, thus attenuating the decrease in CO2. That’s a classic negative feedback loop, moving “the throttle” in either direction.
Your body is chock full of negative feedback systems. For example, consider what is involved if you’re just standing in one place. If you start to tilt to the right your body senses it, and tweaks your muscles slightly, lifting your left foot a tiny bit, to shift a bit of weight from the left foot to the right, to make you lean a little more to the left. If you start to tilt to the left, your body will shift your weight to the left foot, to tilt you more to the right. (And it works the same way in the front-back axis: if you start to lean forward your body will tense the muscles in your feet, to shift weight from your heels to the balls of your feet, but if you start to lean back it’ll do the opposite.) That’s negative feedback, moving “the throttle” in whatever way is needed, to keep you upright.
Note that feedback in a feedback system doesn’t need to be linear. Linear feedback systems are the easiest to analyze, but many feedback systems, both natural and human-engineered, are non-linear. For a simple example, consider the thermostat in your house. It is highly non-linear. Most home thermostats are binary or trinary (with a bit of hysteresis to avoid excess cycling, which is inefficient and hard on motors and compressors). They just turn your heat or a/c on or off, as necessary, to keep temperatures within a relatively narrow range. (They sometimes also have an auxiliary heater which they can trigger, on particularly cold days, if the main system is not keeping up with the load.)
In engineering, “overshoot” is usually undesirable, though a little bit of overshoot may be tolerable. What usually happens is that if there’s a delay in the feedback look, as you dial up the feedback gain, the system becomes increasingly responsive to, but also tends to become increasingly unstable, resulting in overshoot or even oscillation. If you can’t reduce the delay in the feedback loop, then simplest remedy may be to simply to dial back the amount of proportional negative feedback. But a better solution is often to augment the negative proportional feedback with a bit of negative derivative feedback (the “D” in “PID” which stevefitzpatrick mentioned). That’s a great way to improve system stability and reduce overshoot, without compromising system responsiveness.

Sorry, it’s past my bedtime, I’m getting sloppy.
“What usually happens is that if there’s a delay in the feedback look, as you dial up the feedback gain, the system becomes increasingly responsive to, but also tends to become increasingly unstable, resulting in overshoot or…”
should be:
“What usually happens is that if there’s a delay in the feedback loop, as you dial up the feedback gain, the system becomes increasingly responsive, but also tends to become increasingly unstable, resulting in overshoot or…”

Willis,
I was agreeing with Dave when he wrote this: “Negative feedback mechanisms can only attenuate a forcing, Bill (or cause oscillations if delayed). They can’t reverse the sign of a forcing.”
Control theory is well known and widely used, including your example of an engine governor, which can indeed be based (and often is based!) on simple negative feedback. I think you are mistaken when you suggest that increasing albedo with increasing ocean temperatures (above~25C) is something more than a negative feedback.
BTW, your data show that cloudiness increases when temperatures are lower than 25C, which would indicate an unstable positive feedback if the only impact was reflection of light. Since higher latitudes do not “run away” towards colder temperatures, the system has to be more complicated than one where temperature is regulated by albedo. Clouds have a net cooling effect only where the energy in the sunlight they reflect is more than they reduce infrared energy loss to space. Your graphic of albedo versus temperature (which is very interesting) seems to be showing that clouds have net cooling (negative feedback) at low latitude, where there is lots of sunlight, and net warming (positive feedback) at high latitude, where there is much less sunlight.

The climate models and the theory assume there is +0.7/W/m2 of cloud feedback forcing per +3.7 W/m2 of increased GHG forcing while these numbers for the tropics say it should really be -17.5 W/m2 per +3.7 W/m2 of GHG forcing.

Bill, In actuality the 1C would never be realized. As the temperature started to respond to the 3.7 W/m2 of forcing the temperature would begin to rise. As the temperature went up the first 0.01C the feedback would kick in with .6 W/m2 reduction leaving only a 3.1 W/m2 surplus. When the temperature went up .05 C the feedback would kick in with a 3.0 W/m2 reduction leaving only a 0.7 W/m2 imbalance. When the temperature rose a whopping 0.062 C, the feedback will exactly balance the increase from CO2. 0.062C is not a very scary number at all. My body temperature probably varied by more than that while I calculated the balance point!

…I have hypothesized elsewhere that variations in tropical cloud albedo are one of the main mechanisms that maintain the global surface temperature within a fairly narrow range …
Sounds likely. Also sounds very reminiscent of the ‘DaisyWorld’ mechanism proposed by Lovelock – http://en.wikipedia.org/wiki/Daisyworld
But, of course, it has a fundamental difference. Lovelock’s hypothesis was that lifeforms themselves provided the feedbacks necessary to maintain an appropriate environment for life – and you are pointing out that purely mechanistic processes seem to do this for us…

Monthly averages are certainly informative, but the proposed mechanism would appear to operate at much smaller timescales (i.e. hourly). I would expect that the relationship would resolve much more clearly with more granular data.
The data challenge will be that, unlike months, it’s not the same hour everywhere at the same time.

ren, I’ve observed more evaporation, ie, clouds, water vapor, and IR, in satellite images when solar flux goes high for a few weeks vs when it goes low for a few weeks, as it has over the past several solar rotations. If i can find the time, I’ll make some animations to illustrate. Probably fits in with this post in some way.

First, your Great Lakes point is just a little North and East of where I live (thank!, N41W81).
Second point, all of that water is transported poleward, there should be some sign of it showing up as an increase of warm humid air, and maybe a higher albedo. This might not be apparent at the great lakes even though we have two summer climates, Warm humid Gulf air, and cool Canadian air.https://micro6500blog.files.wordpress.com/2015/05/may-8th-26th-2015.png

“The albedo data is thus strong support for my hypothesis that the timing and strength of the daily onset of the tropical cumulus and cumulonimbus regimes exercises a strong control on the amount of incoming energy.” — Willis
Woah there, Sparky. Results are either consistent or inconsistent, full stop. I do not and have never bought into the ‘Best Available Evidence’ arguments in support of underspecified metaphysical models. Undeniably this is consistent with your metaphysic and, indeed, predicted by it.
But more important is that any model or metaphysic that *cannot reproduce* the correlations demonstrated is *incomplete or inconsistent* with observation. Which are two different ways to say that such a model is *wrong.*
The interesting question then is whether or not the GCMs can produce this correlation, as every single one that cannot must be discarded. Or must put some freaking massive error bars on their results.

Willis, have you ever thought of putting all your writings on climate into one book (pdf). I would certainly buy it. It would be really useful if such a document were divided into sections by topic rather than a chronological presentation. I find your explanations and diagrams very clear and easy to understand and above all, your logic is impeccable.
Long may you continue.

http://nsidc.org/greenland-today/files/2014/06/Figure3.png
Albedo has ranged as high as 34 to 35% during recent Ice Ages. As shown through the Greenland Ice Cap albedo values ,any expansion of ice and or snow will have an impact on global albedo, in addition to changes in cloud coverage.
The last century’s feature of stable climate conditions being more the exception then the rule, and is not representative of how stable /unstable the climatic system really is. A very misleading century to show stability in the climate system, in contrast to the Younger Dryas period as an example which would give a much different picture.

Top: The total daily contribution to the surface mass balance from the entire ice sheet (blue line, Gt/day). Bottom: The accumulated surface mass balance from September 1st to now (blue line, Gt) and the season 2011-12 (red) which had very high summer melt in Greenland. For comparison, the mean curve from the period 1990-2011 is shown (dark grey). The same calendar day in each of the 22 years (in the period 1990-2011) will have its own value. These differences from year to year are illustrated by the light grey band. For each calendar day, however, the lowest and highest values of the 22 years have been left out.http://www.dmi.dk/uploads/tx_dmidatastore/webservice/b/m/s/d/e/accumulatedsmb.png

Willis: I’ve been doing “back of the envelope” calculations ever since you came up with the “thunderstorm thermostat hypothesis”. I think you are getting close to a “breakthrough paper”. I have this SNEAKING suspicion that the DATA is there, and it just needs to be processed correctly to verify that TS’s are the prima facia negative feedback mechanism. Now this isn’t quite as strong as what I’m hoping you will find, but do you remember Svensmark’s “Forebush Decrease” paper, correlating cloud cover, with a decrease in cosmic rays caused by a large solar flare? I think YOU may be able to find as strong a correlation as that in the existing data, or BETTER. In which case, 400, 500, 600, maybe 1000 to 2000 PPM is “non-sequitur” (of CO2 that is). By 1000 PPM, the Star-ship Enterprise is using Antimatter propulsion and the CO2 argument is MOOT anyway.

Looking at figure 5 some more, from May to September the system is tightly constrained with small variations. From September to May it goes on a grand excursion of large variations. It is suggested that the system slows before a regime change. The guessed at regime change is the hard negative feedback in the Pacific equatorial region at about 26 C. In figures 6 and 7 there is this apparent slope change. When the slope passes through zero and takes the opposite sign, there’s your daily dragon king.

Excellent, Willis, one of your best. But I think you should have saved it for a journal publication. It builds on the Iris Effect, with lots of new info.
Glad you posted it here, though. Who knows how long climate peer review would take?

Nice, thought provoking work as usual, and nicely presented. Many thanks, Willis.
The albedo feedback doesn’t surprise me, though it is very nice to see it analysed like this, but the close similarity of NH and SH albedo is completely unexpected. The data you show is averaged 2000-2014, I note. If we take individual years, or shorter time increments, is there much more variability?

“the close similarity of NH and SH albedo is completely unexpected”
Not really. There is strong theoretical reasons to expect the ITCZ to move towards the warmer hemisphere (and equally good observational data to confirm that it does, this is known as “monsoon”), and since the ITCZ has very high albedo this has a strong balancing effect on albedo.

Correct.
But note that latidinal shifting of the ITCZ also involves a proportionate shift in all the latitudinal climate zone boundaries between equator and poles.
It is that latitudinmal shifting that represents the negative system response to ANY forcing element that seeks to disturb the net radiative balance with space.

Thank you Willis good read and great graphics enhancing the reading. Advancing our understanding of such things.
Off track, but we used to get similar figures to your Figure 5 when we plotted discharge during a runoff event on the x-axis and suspended sediment concentration on the y-axis. They both started at zero and the sediment concentration was quite high until after the peak of the hydrograph and much lower during recession back to zero at the end of the runoff. We called it hysteresis. It showed the higher energy slope on the rising limb compared to the lower energy slope on the recession. No periodic functions involved just runoff and sediment concentration in ephemeral stream flow.

We see this in biology too when we construct variable-variable plots of data that we know is related within the system. As example: angle at ankle versus angle at knee during locomotion. We call them return plots as they cycle away from and back to origins. There is considerable variability in those plots, just as yours, but within some envelope there is “homeostasis”.
Of course, in our work there are functional limits beyond which the organism fails or becomes injured. There are also feedbacks – all negative – toward preventing injury.
One of the thoughts that I come to is that Global Ave T and CO2 are not correlated. They simply do not cycle with each other.
Very nice work, Willis.

First-rate look at things, Willis!!!
Consider the effect of the floating “Ice-Doughnut” around Antarctica – at record levels (>20 million sq/Km last September), and breaking records ever since on a monthly basis! Here’s the effect: 1 – Cloud cover near the edges of the “doughnut” increases as the presence of sea-ice makes water vapor condensation more likely. 2 – An increasing radius of cloud cover around the “doughnut” increased the “albedo zone” surrounding the Antarctic. 3 – The result is “flipping” the albedo, from 80% absorbing ocean to 70% reflecting cloud/ice/snow, and the reflectivity occurs at mostly shorter wavelengths that CO2 cannot intercept and re-direct.
The planet’s air temperature HAS to get colder as a result, even in the face of rising CO2, and that is exactly what we observe.

That “hook” a bit over two-six
Rang a bell, a connection that clicks
It’s the temperature zone
That will cause a cyclone
One of many cloud/temp-control tricks:http://www.aoml.noaa.gov/hrd/tcfaq/A16.html
===|==============/ Keith DeHavelle

It is interesting to note that on land albedo and temperatures are usually negatively correlated. This is easy to understand, colder means more light-coloured clouds (or even snow) while warmer means more dark vegetation.
There is however a striking exception. Areas on the edge of deserts are positively correlated. Presumably this is because higher temperature here means that it becomes so dry that vegetation withers and albedo rises.

We need to be careful about albedo. Take a sphere which is notionally a blackbody, at thermal equilibrium with its surroundings. Measure and record its temperature. Now paste a small two-sided perfectly reflecting mirror on its surface. It reflects some incoming radiation outward, but it also reflects the same amount of outgoing radiation inward, because at equilibrium outgoing radiation must equal incoming. The temperature of the sphere with the mirror in place will be the same as it was before the mirror was added. And, it will remain the same no matter how many mirrors are placed on its surface. Ultimately, a fully mirrored sphere will still have the same temperature as the blackbody. All of the partly mirrored spheres are what is called “greybodies.” They are reflective but still colorless. All of them follow the Stefan-Boltzmann radiation law. Now, if the surface of the earth is a greybody, and a cloud is also a greybody, the presence of the cloud will have no effect on surface temperature.
As a practical matter, both the surface and the cloud are nearly, but not quite greybodies so that the presence of a cloud will have some effect. Low clouds are supposed to be cooling and high clouds warming. But not the major effect imagined by some who visualize the earth being shielded from radiation whatever the altitude, because the cloud also acts as an insulator, reflecting outgoing radiation downward and suppressing convection.
As a side issue, placing both of these spheres in a temperature controlled oven will cause them both to come to the temperature the oven is set at, but they will approach this temperature at different rates. This comes from Kirchoff’s Radiation Law which applies when the source, the sink and the test body are at the same temperature. With the sun – earth – space system, a body on the surface of the earth is never in thermal equilibrium, so color (deviation from the blackbody spectrum) does matter.

Those mirrors are a poor model for the stuff of the Earth’s atmosphere, Pochas. Instead of placing “perfectly reflecting mirror[s]” which reflect the same amount of incoming and outgoing radiation, place something in the atmosphere which has a differential effect on incoming vs. outgoing radiation, and you get a very different result. That’s what GHGs do. Over half of the incoming radiation (from the Sun to the Earth) is visible or shorter wavelengths, but nearly all of the outgoing radiation (exiting the Earth) is IR or longer wavelengths. So if you put something in the atmosphere which affects the transmission of some wavelengths more than others then the result will be that the surface warms or cools.

daveburton,
CO2 blocks 15u outgoing but that leads to more vigorous convective overturning.
The ascending columns push higher to a colder location and that colder air enters the descending column.
In adiabatic convection the initial temperature differential is maintained all the way up or all the way down so in the ascent the lapse rate slope is distorted to the warm side but in the descent the slope is distorted to the cool side by an equal and opposite amount.
The net thermal effect at surface and tropopause being zero.
The descending column contains the blocked 15u in the form of potential energy which heats the surface and the surface then radiates at the full range of wavelengths so as to defeat the initial blocking effect.
Convective overturning accelerates precisely as much as necessary to get the 15u blocked by CO2 out to space from the surface at other wavelengths.
The only effect of GHGs is to distort the lapse rate slope equally and oppositely in ascent and descent.

Stephen Wilde wrote, “The descending column contains the blocked 15u in the form of potential energy which heats the surface and the surface then radiates at the full range of wavelengths so as to defeat the initial blocking effect… The only effect of GHGs is to distort the lapse rate slope equally and oppositely in ascent and descent.”
That’s all wrong, Stephen. The potential energy gains and losses are balanced by rising and falling air columns, but that has nothing to do with the absorption of 15µ IR by atmospheric CO2, which warms the air regardless of whether it is rising or falling, and it certainly doesn’t “defeat” the absorption of IR by GHGs in the atmosphere.
(It also has nothing to do with the the latent heat [heat of evaporation] which is transported aloft by the water cycle. When water evaporates at ground level, it absorbs latent heat, cooling the ground. When the water vapor condenses in clouds it releases latent heat, which warms the atmosphere at that altitude.)
When the rain or snow falls, there’s some potential energy converted to kinetic energy, but most of it is lost via friction to the air, still high in the atmosphere. You can tell that by the fact that raindrops and snow flakes fall, for most of their trips to the surface, at very near their terminal velocities.
Have you never noticed how the temperature drops during a cloudburst? If the falling raindrops & surrounding air were carrying lots of (kinetic) energy back to the ground, then the ground would get warmer, rather than cooler, during a cloudburst.

daveburton,
Colder air reaches the surface benearh a cloudburst because rising warmer air has mixed with colder air aloft and the colder air descends rapidly to the surface. The air in the cloudburst being colder than its surroundings is a result of the higher colder air having been transported horizontally from a colder location and is a separate phenomenon to adiabatic cooling in uplift or warming in adiabatic descent.
I agree therefore that the latent heat of evaporative cooling is nothing to do with adiabatic cooling and I note from your previous post that it is you who think they are interchangeable.
Evaporative cooling fuels the phase change of water from liquid to vapour and cooling in adiabatic ascent is entirely separate.
Lifting air to a higher location involves both lifting against the force of gravity and allowing expansion to occur against the intermolecular attractive forces between molecules. Both involve creation of PE at the expense of KE which is why gases create vastly more PE in uplift against gravity than do solids or liquids which expand hardly at all.
The blocking of 15u does indeed warm air whether it is rising or falling but the net effect for the globe as a whole is to accelerate ascent in rising columns thereby distorting the lapse rate slope rather than heating the surface. At any given moment 50% of the atmosphere is rising and 50% is falling relative to the horizontal plane.
Accelerated ascent pushes higher above the tropopause to a higher colder location so that higher colder air feeds into the descending column.
Since adiabatic uplift and descent preserve the intial temperature differential through the whole column (no energy allowed in or out of the moving parcel) the entire descending column becomes cooler than it otherwise would have been.
The temperatute differential is maintained in adiabatic uplift and descent because the rising or falling parcel cools or warms at the same rate as the surroundings.
There is leakage of energy in and out via separate diabatic processes but that does not eliminate the temperature differential otherwise the parcel would stop rising before it treaches the tropopause or stop falling before it reaches the ground.
Kristian remains under the incorrect impression that the diabatic exchange with the surroundings is the adiabatic process. He needs to rethink that.
In reality it is common for rising air to fail to reach the tropopause or falling air to fail to reach the ground but those are local irregularities within the general phenomenon of convection being all pervasive between surface and tropopause.
Meteorology is a specialist discipline and has been overlooked by AGW theory.

The problem is the cloud mirrors respond to an increase in their temperature by rising in altitude and releasing the energy back to space. Also a mirror above the surface particularly one which is not truly gray, but has transparencies and reflectances at different colors and the exact positioning and width of those colors depends explicitly on temperature, has a distinctly different effect. If for instance the incoming radiation is from a 3500K blackbody which the mirror 80% reflects and the surface gray body radiates at 300K which the mirror only reflects at 50%, then the surface gray body will cool significantly.

Well, I must hold on to this, pochas, and think about it, thanks. It speaks to the conundrum raised when we realised, some of us, that known planetary atmospheres obeyed the gas laws for their pressure range. This is apparently irrespective of different albedic effects as well as gas specie, even all CO2. Brett

“But not the major effect imagined by some”
You forget that the clouds are very largely convective, i. e. they are due to convective upward heat transport. This is actually the dominant form of upward heat transport, almost twice as important as LWIR.

Stephen Wilde wrote, “that work done against gravity in the ascent creates potential energy which does not escape but which returns to the surface in the next descent.”
Moist air rises because it ls lighter (less dense) than drier air, because water vapor is only (1+1+16) / ((.78 * 28) + (.21 * 32) + (.01 * 40)) = only 62% as dense as dry air. As a column of moist air rises, surrounding drier air falls. So I think the work is being done evaporating the water at the surface, not during the ascent of the moist air.

Energy is taken up in the phase change but work is done throughout uplift.
Being lighter than air water vapour requires less work to be done for a given height than dry air would but work is done against gravity nonetheless and that creates potential energy (not heat) in place of kinetic energy (heat).
It is the work done in uplift that creates the temperature decline with height along the density gradient, not radiation to space from the GHGs as proposed by AGW theory.

Stephen, please read your own link. It says the exact opposite of what you seem to be claiming. As always … Have a look at Figure 9.6 for instance. What does it say? What does it show? You still don’t comprehend that basic distinction between macroscopic (mechanical) energy, having to do with the motion/position of the system as a whole, and microscopic (internal, thermodynamic) energy, having to do with the system’s temperature. Your KE/PE conversion only affects the former. The adiabatic cycle deals with the latter – through expansion/contraction against a varying external pressure. You just don’t want to get this. It is so fundamental, Stephen. Everyone and anyone with only a little bit of meteorological training understands how this works. You and Doug Cotton don’t. You simply don’t. And we all see it. We have now for quite some time.
The surface heat isn’t brought back to the surface, Stephen. It is radiated to space. This is how the climate system operates.

Stephen, please read your own link. It says the exact opposite of what you seem to be claiming. As always … Have a look at Figure 9.6 for instance. What does it say? What does it show? You still don’t comprehend that basic distinction between macroscopic (mechanical) energy, having to do with the motion/position of the system as a whole, and microscopic (internal, thermodynamic) energy, having to do with the system’s temperature. Your KE/PE conversion only affects the former. The adiabatic cycle deals with the latter – through expansion/contraction against a varying external pressure. You just don’t want to get this. It is so fundamental, Stephen. Everyone and anyone with only a little bit of meteorological training understands how this works. You and DC don’t. You simply don’t. And we all see it. We have now for quite some time.

Kristian,
9.6 does indeed also deal with diabatic energy movement into and out of the rising or falling parcel. You need to involve both diabatic and adiabatic processes to get Total Energy (TE).
The diabatic energy exchange is separate from the adiabatic process which latter involves work done with or against gravity.
The adiabatic process is the one that involves conversion of energy to and fro between KE and PE within the parcel.
The process that involves energy moving into or out of the parcel is a diabatic process as I keep telling you.
Work done against surrounding molecules is diabatic and energy does then move in and out.
Work done with or against gravity is adiabatic and energy is transformed within the parcel between KE and PE and does not move in or out.
You really need to grasp that because apart from that single point much of your thesis is correct.

“You forget that the clouds are very largely convective, i. e. they are due to convective upward heat transport. This is actually the dominant form of upward heat transport, almost twice as important as LWIR.”
tty, bulk air movement is not the ‘dominant’ form of heat transport within the troposphere. It is effectively the only form of heat transport within the troposphere. Conduction, evaporation/condensation and radiation basically constitute heat transfers into and/or out of the troposphere. Inputs and outputs. The internal throughput, from the ‘heating (absorbing) end’ to the ‘cooling (emitting) end’, inside the troposphere, is by convective transfer.

Kristian said:
“The internal throughput, from the ‘heating (absorbing) end’ to the ‘cooling (emitting) end’, inside the troposphere, is by convective transfer.”
In the absence of GHGs (or any radiative capability in the atmosphere at all) the surface is both the heating end and the cooling end.
To deal with that you need to get the energy holding up the atmosphere in hydrostatic balance back to the surface fast enough for radiation from the surface to space equal to radiation to the surface from space.
My (standard and established) version of the adiabatic process achieves that whereas your version does not.

daveburton
The evaporation of water creates the density difference between the two air masses, but work done requires movement of mass.
Physical definition of Work:-
The work done on a given mass is the result of the force applied times by the distance moved by the object.https://en.wikipedia.org/wiki/Work_(physics)

There is some balancing as the rising air is replaced at the surface by dry air from altitude, net work may be close to 0. The moist air rises until condensation happens (then may rise some more) the heat from the condensation is then released into the air as the water condenses out.
The question is what is the temperature radiating from the cloud top. It is quite cool (I’ve heard this argument many times as support for why this is all poppycock), but how cold is the surrounding air at the same pressure altitude? My suggestion is that the top of the thunderhead is likely warmer than the surrounding air, the clear air is just much harder to measure because the signal is swamped out by the clear view of the warmer ground.

Willis said:
“Now, this is most interesting. The warmer the ocean gets, the lower the albedo goes, a negative correlation … except when the temperature gets over about 26°. Above that, the warmer it gets, the higher the albedo goes”
General meteorology deals with that.
The lowest albedo near the equator, with least clouds, is beneath the subtropical high pressure cells which contain descending columns of dry air.
Due to the absence of clouds albedo is low and so more solar energy gets into the oceans and the temperatures rise so in such locations a low albedo is associated with higher temperatures.
Since the descending air is dry the surface temperature over the oceans is controlled by evaporation which cools the surface somewhat but that increases humidity. The humid air cannot rise into the descending column so it flows outwards towards the nearest low pressure cell containing rising air.
The ITCZ is a primary source region for lower pressure and ascending air so the humid air flowing in from below the adjacent high pressure cells rises within the ITCZ to give increased albedo.
26C is the point at which the warmth of the ocean surface plus the greater buoyancy of humid air reliably defeats the weight of the mass of the atmosphere above so as to allow extensive convection as per Willis’s Tropical Thunderstorm Hypothesis.
However, that hypothesis is only a small part of the global convective system which is regulated more generally by latitudinal climate zone shifting rather than simply thunderstorm generation in the tropics.
Willis’s hypothesis also fails to explain how the convective system can prevent GHG warming in the absence of water vapour so it is does not provide a full rebuttal for AGW theory.
I say that water vapour only makes it easier for the convective system to maintain thermal stability. In the absence of water vapour the convective system will still maintain stability but needs to work harder (faster) in order to do so.

“The albedo data is thus strong support for my hypothesis that the timing and strength of the daily onset of the tropical cumulus and cumulonimbus regimes exercises a strong control on the amount of incoming energy.” — Willis

Woah there, Sparky. Results are either consistent or inconsistent, full stop. I do not and have never bought into the ‘Best Available Evidence’ arguments in support of underspecified metaphysical models. Undeniably this is consistent with your metaphysic and, indeed, predicted by it.

Thanks, Jquip. I’m not sure what you mean by my “metaphysic”. In fact, until you mentioned it I was unaware that I had unknowingly acquired an “unspecified metaphysical model”.
I do have a hypothesis that makes some testable predictions. The hypothesis is that a variety of emergent phenomena act in concert to regulate the temperature. One testable prediction is that in the tropics, the clouds will act in opposition to the incoming sunlight by increasing reflections with increasing temperature..
And when I look, guess what I find? Just what the hypothesis predicted. This is often called something like “support for the hypothesis”. And as you pile up enough different kinds of support, you gain confidence that the underlying hypothesis is valid.
For example. If my hypothesis was “I can use astrology to predict the stock market”, if I used the system and made big money every year for fifty years … that would be support for the hypothesis. It wouldn’t be called “consistent with the possibility that the hypothesis might be valid”.
Having said that, at the core in a strict sense you are 100% correct. My finding supports ANY hypothesis which might make the same prediction, not just mine … if you have any other hypotheses that make the same prediction, let me know. Me, I’m just looking to pile up what I’ll continue to call “the supporting evidence”.
Best regards, and thanks for the comment.
w.

I’m not sure what you mean by my “metaphysic”. In fact, until you mentioned it I was unaware that I had unknowingly acquired an “unspecified metaphysical model”.

Metaphysic as in the basic nature of things, their properties, manners in which they change, etc. It’s all loosey-goosey-gassey stuff that’s your preference of ‘informal’ or ‘nonmathematical.’ And the unknowing acquisition of yours was: underspecified metaphysical model.

And as you pile up enough different kinds of support, you gain confidence that the underlying hypothesis is valid.

Yes, there is often a fallacious use of Bayesian reasoning that follows this line of thought. Occasionally you’ll find people put Hempel’s Raven into use to cover over an argument from ignorance on the same point. And barring a very specfic set of caveats the claim is absurd whether it’s made by you, Mann, or Feynman.

My finding supports ANY hypothesis which might make the same prediction, not just mine …

Your finding is consistent with ANY hypothesis… More to the point that was made further on in the part you didn’t quote is that any metaphysic, model, hypothesis, theory, law, of navel lint expedition that is not consistent with this finding is inconsistent with reality. A very pedantic way to say: False.
Given that the original context is above, I’ll repeat here: The interesting question then is whether or not the GCMs can produce this correlation, as every single one that cannot must be discarded. Or must put some freaking massive error bars on their results.

I’m not sure what you mean by my “metaphysic”. In fact, until you mentioned it I was unaware that I had unknowingly acquired an “unspecified metaphysical model”.

Metaphysic as in the basic nature of things, their properties, manners in which they change, etc. It’s all loosey-goosey-gassey stuff that’s your preference of ‘informal’ or ‘nonmathematical.’ And the unknowing acquisition of yours was: underspecified metaphysical model.

Sorry, my friend, but that just adds heat without adding light.

My finding supports ANY hypothesis which might make the same prediction, not just mine …

–The albedo of the earth is about 0.29, meaning 29% of the sunlight is reflected back to space. Figure 1 shows the average albedo around the planet.–
It seems to me that an assumption is that clouds [or snow] is considered the same as albedo.
And think a clear sky reflects sunlight.
So if Earth albedo is about 0.29 what would Earth albedo be if Earth had no clouds [or snow]?

Interesting but not necessarily compelling. The number of variables involved make pinpointing causation of effects assumptive despite having a reasonable logic behind the idea.
An alternative theory of oceanic warming and the function of clouds in regards to temperature suggesting direct solar influence is linked below.https://m.youtube.com/watch?v=XdrDg-Nuxdg

Willis: Very interesting data. Unfortunately, over most of the planet, as the temperature warms, albedo decreases about 1% per degC (Figure 4). That about 3 W/m2/K, a massive positive feedback, which when combined with water vapor+lapse rate feedback would produce a runaway greenhouse effect. Fortunately, all clouds are not created equal. High cold cirrus clouds warm the earth and low warm boundary layer clouds cool the earth. Does CERES also record data on cloud top temperatures?
Others have noted averaging smears out important features. An ITCZ which is probably 10 degC wide in any one month marches 30-40 degrees north and south every year, with the descending branches of the Hadley circulation moving in parallel. I suspect the plots for any one month of the correlation between albedo and SST will have many more features

Rob JM wrote: The increased cooling at night time [at high latitudes] MAY outweigh the increased warming in daytime.
Good point, but the key word is MAY. The data to answer that question is probably known. An old answer can be found at the link below. Cloud radiative forcing at high latitudes is warming over land and cooling over water. This may happen because land is covered with snow during the winter and albedo is the same with and without clouds.http://www.indiaenvironmentportal.org.in/files/file/cloud%20radiative%20forcing.pdf

Frank said: “High cold cirrus clouds warm the earth and low warm boundary layer clouds cool the earth.”” … highly reflective cirrus clouds are produced which act like a thermostat, shielding the ocean from solar radiation. The regulatory effect of these cirrus clouds may limit sea surface temperatures to less than 305 K.[32°C]””Water vapour and clouds are the dominant regulators of the radiative heating of the planet.””We show that this cirrus regulation of ocean warming is triggered primarily when SSTs exceed 300K. [27°C]“”… the feedback between SST, convection, and cloud reflection of solar radiation prevents a runaway greenhouse effect on the SST and acts as a thermostat to regulate the maximum ocean temperatures on the planet.””It would take more than an order of magnitude increase in atmospheric CO2 to increase the maximum SST by a few degrees, in spite of a significant warming outside the equatorial regions.”
Ramanathan, V., and W. Collins 1991. “Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Nino.” Nature 351.6321 (1991): 27-32.http://lightning.sbs.ohio-state.edu/geog5921/paper_thermostat_Ramanathan1991.pdf

Brian: Thanks for the reference, but it may be out of date. My main point was that high and low clouds reflect incoming SWR (albedo in this post), but have different effects on OLR based on their altitude. Clouds block OLR from below, but the amount of radiation they emit towards space and the surface depends on their temperature and therefore their altitude. The paper you cite comes from the early days of satellites, when the magnitude and even sign of cloud radiative forcing (ie do they make the earth cooler or warmer?) was conclusively measured for the first time. I skimmed this paper and saw no conclusive evidence that the effects of clouds were due specifically to cirrus clouds.
According to NASA (http://earthobservatory.nasa.gov/Features/Clouds/)
“The study of clouds, where they occur, and their characteristics, play a key role in the understanding of climate change. Low, thick clouds primarily reflect solar radiation and cool the surface of the Earth. High, thin clouds primarily transmit incoming solar radiation; at the same time, they trap some of the outgoing infrared radiation emitted by the Earth and radiate it back downward, thereby warming the surface of the Earth. Whether a given cloud will heat or cool the surface depends on several factors, including the cloud’s altitude, its size, and the make-up of the particles that form the cloud. The balance between the cooling and warming actions of clouds is very close although, overall, averaging the effects of all the clouds around the globe, cooling predominates.”
Since WIllis’s post looks at correlation only between albedo and surface temperature, he is looking at only the effect of clouds on SWR and ignoring their effect on OLR.
Lindzen discusses the different properties of thin cirrus clouds, thick cirrus clouds and boundary layer clouds in the tropics here:http://www.atmos-chem-phys.net/2/99/2002/acp-2-99-2002.pdf
“Cirrus clouds reduce both the longwave cooling and short- wave heating of the Earth. The magnitude of these two com- peting effects depends on the optical thickness of the clouds. Thin cirrus with an optical thickness of, say < 1, in the vis- ible spectral region are relatively transparent to shortwave radiation but not necessarily transparent to the longwave ra- diation. Thus, thin cirrus clouds have a stronger longwave warming effect than a shortwave cooling effect, which leads to a net warming effect on the climate. On the other hand, thick cirrus clouds are highly reflective to shortwave radia- tion and generally have a net cooling effect on the climate. The overall effect of cirrus on the Earth radiation budget de- pends strongly on the areal coverage of thin cirrus clouds relative to that of thick cirrus clouds."
New evidence consistent with Lindzen's iris hypothesis was discussed recently at Climate Etc.http://judithcurry.com/2015/05/26/modeling-lindzens-adaptive-infrared-iris/
"He then observed that low humidity regions were cirrus ‘deficient’, while high humidity regions were cirrus ‘surplus’. (Cirrus clouds have an inordinate impact on ‘greenhouse effects’. These high thin ice clouds have low ‘short wave’ albedo so are nearly transparent to incoming sunlight, while high albedo and nearly ‘opaque’ to outgoing long wave (infrared) radiation–simply because cirrus clouds are comprised of ice crystals. Cirrus indisputably net warms.)"
I'm not an expert in this area, so I'm not sure you can't find some new references that disagree with some aspects of the references I cite. However, I would be very surprised to learn that low clouds don't cool the planet more than higher ones

Frank says : ” However, I would be very surprised to learn that low clouds don’t cool the planet more than higher ones”
I second your comment. A 60 watt per sq meter shift is huge, about 5% of the total input from the sun, all in the space of an hour or two.

Excellent thought provoking post Willis.
But can you or anyone else explain to ignorant me, how the albedo decreases with a rise in ocean temperature (what mechanism) I understand the after 26C bit, but it is the before I can’t understand.

“[A governor is not a feedback mechanism.] In the current context, a governor is a mechanism that controls the throttle of a heat engine in order to set it to some specified operating condition. For example, the “cruise control” in a car is an example of a governor. It is… not a simple feedback. The governor can push the throttle either way. Simple negative feedback can’t do that.”

Ooooh, bad Dave. I NEVER SAID “a governor is not a feedback mechanism”, and I strongly object to your mischaracterization. I asked you to quote my words exactly, not paraphrase them. I can defend my own words, as I choose them quite carefully. I cannot defend your interpretation of my words.

Actually, a cruise control is very commonly used in engineering classes and texts as an example of a feedback system.

What I said was that a governor is a different thing than a simple feedback. For example, what is the name of the object with the round balls in the center of this photo?https://wattsupwiththat.files.wordpress.com/2014/07/tva-flyball.jpg
It is called a “flyball governor”. It is not called a “flyball feedback”. There’s a reason for that—it’s a governor, not a feedback. I’m not sure why folks find this distinction so objectionable, as it has a long and honorable history clear back to Big Jim Watt …
Best regards,
w.

Willis quoted me saying, “A governor is a feedback mechanism,” and he replied, “I’m sorry, but that’s not so.”
I paraphrased that as, “[A governor is not a feedback mechanism.]…”
To that, Willis cried foul, writing, “Ooooh, bad Dave. I NEVER SAID “a governor is not a feedback mechanism”, and I strongly object to your mischaracterization….”
Really? If saying it is “not so” that “a governor is a feedback mechanism” doesn’t mean “a governor is not a feedback mechanism,” then what does it mean, Willis?

Willis also wrote, “[the device in the picture] is called a “flyball governor”. It is not called a “flyball feedback”. There’s a reason for that—it’s a governor, not a feedback.”
Willis, a flyball centrifugal governor is another classic example of a human-engineered feedback mechanism. The engine speed is the output, which is fed back through the mechanism of the flyballs, to adjust the governor. As the engine speed increases, the balls fly further apart, decreasing the throttle. As the engine speed decreases, the balls retract, increasing the throttle.
That’s exactly what negative feedback is.Google finds many documents in which a flyball governor is cited as an example of an early, human-designed, feedback system. Here’s one from a text used in a CalTech course entitled, Analysis and Design of Feedback Systems. On page one, which is entitled “Introduction / What is Feedback?” we read, “An early example of a feedback system is the centrifugal governor, in which the shaft of a steam engine is connected to a flyball mechanism that is itself connected to the throttle of the steam engine…”

Wonderful analysis. However, it is also necessary to consider night time behaviors, which your data don’t address. Deserts with clear sky (and parts of the ocean) at night lose lots of heat. I believe this is part of the Iris theory.

“Figure 3.
As you can see, the northern hemisphere land towards the poles is strongly negatively correlated with temperature. This is because as the northern land warms, the ice and snow melts and the plants grow. Both of these changes lower the solar reflectivity (albedo). In the tropics, on the other hand, there are a number of large areas that are positively correlated with temperature.”
While in the horse latitudes there are number of areas that are negatively correlated with temperature, now why would that be?

Willis, I believe you will find support for your “set point” in geological climatic data. There is considerable evidence (e.g. http://www.scotese.com/climate.htm) that there has been an upper limit on global temperature throughout the Phanerozoic. The link above indicates a general boundary of about 25 deg C. I know that just recently a paper was published that argued a boundary at about 30 deg C, which remains consistent with Paleomap Project estimate. Unfortunately I seem to have misplaced the link. I have speculated that the boundary is an equilibrium point that is reached between ocean surface temperatures, surface evaporation, and cloud formation. That might indicate that clouds do act as a governor system for terrestrial climate as you have argued before.

Willis, on May 14, 2015 you wrote an excellent blog about the “Temperature field”. You showed that the annual surface temperature profile of the earth can be represented very well by a fit to the sun shine (TOA) and elevation. In terms of a simple climate model one would attribute this to an albedo which is independent of the latitude. In this blog you show that the Ceres data have a distinct dependence on latitude. So I don’t understand why your fit is working so well.

For permission, contact us. See the About>Contact menu under the header.

All rights reserved worldwide.

Some material from contributors may contain additional copyrights of their respective company or organization.

We use cookies to ensure that we give you the best experience on WUWT. If you continue to use this site we will assume that you are happy with it. This notice is required by recently enacted EU GDPR rules, and since WUWT is a globally read website, we need to keep the bureaucrats off our case!
Cookie Policy